Vehicle electrification has emerged as a promising solution for clean and efficient transportation. Limited driving range of electric vehicles (EV) is a major constraint which hinders its widespread acceptance. One of the most effective approaches to improve an EV’s driving range and performance is utilization of regenerative braking (RB). During RB, the kinetic energy of the vehicle is recaptured, which can then be stored in the energy storage system. It is estimated that the average range of EV can be extended by around 15% with the use of RB. Hence, efficiency of the RB process is one of the key factors that influences the range of EV. Over the years, industry and academic research have led to the development of different approaches to improve energy regeneration during the braking process. One of the constraints that limits the RB efficiency is its inability to regenerate under low-speed conditions. When the vehicle velocity falls below a certain threshold, due to insufficient back- electromotive force (emf) developed in the traction motor, energy begins to be extracted from the energy storage system instead of being returned, resulting in additional loss. As per literature, most approaches proposed to improve regeneration efficiency have not considered the above limitations. In a few of the reported studies, a constant low-speed threshold has been considered for RB, below which RB is disabled. However, this low-speed threshold is a dynamically varying quantity that depends on driver command, driving conditions, and parameters of motor, battery and cables. Although methods implemented to determine dynamic low-speed threshold are reported to result in higher braking efficiencies than fixed point methods, former implementations typically involve dynamic detection of battery current direction, which poses sensing challenges due to factors such as current sensor accuracy, offset, filtering and delays. As an alternative method, this work proposes a model-based approach to analytically determine the dynamic low-speed cut-off point (LSCP). Additionally, a loss minimization framework is proposed, to enhance the amount of energy recovered by achieving a lower value of the cut-off point, thereby extending the braking duration. Further, enhanced control strategies for regenerative braking which helps to improve energy regeneration efficiency and maintain stability of the vehicle, simultaneously.